Abstract
In this study, we present a sensorless, robust, and physiological tracking control method to drive the operational speed of implantable rotary blood pumps (IRBPs) for patients with heart failure (HF). The method used sensorless measurements of the pump flow to track the desired reference flow (Q(r)). A dynamical estimator model was used to estimate the average pump flow ((Q) over cap (est)) based on pulse-width modulation (PWM) signals. A proportional-integral (PI) controller integrated with a fuzzy logic control (FLC) system was developed to automatically adapt the pump flow. The Q(r) was modeled as a constant and trigonometric function using an elastance function (E(t)) to achieve a variation in the metabolic demand. The proposed method was evaluated in silico using a lumped parameter model of the cardiovascular system (CVS) under rest and exercise scenarios. The findings demonstrated that the proposed control system efficiently updated the pump speed of the IRBP to avoid suction or overperfusion. In all scenarios, the numerical results for the left atrium pressure (P-la), aortic pressure (P-ao), and left ventricle pressure (P-lv) were clinically accepted. The (Q) over cap (est) accurately tracked the Q(r) within an error of 0.25 L/min.